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distilbert-base-uncased__sst2__train-32-4
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5001
- Accuracy: 0.7650
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7175 | 1.0 | 13 | 0.6822 | 0.5385 |
| 0.6559 | 2.0 | 26 | 0.6533 | 0.6154 |
| 0.6052 | 3.0 | 39 | 0.5762 | 0.7692 |
| 0.4587 | 4.0 | 52 | 0.4477 | 0.8462 |
| 0.2459 | 5.0 | 65 | 0.4288 | 0.7692 |
| 0.1001 | 6.0 | 78 | 0.5219 | 0.7692 |
| 0.0308 | 7.0 | 91 | 0.8540 | 0.7692 |
| 0.014 | 8.0 | 104 | 0.7789 | 0.7692 |
| 0.0083 | 9.0 | 117 | 0.7996 | 0.7692 |
| 0.0064 | 10.0 | 130 | 0.8342 | 0.7692 |
| 0.0049 | 11.0 | 143 | 0.8612 | 0.7692 |
| 0.0036 | 12.0 | 156 | 0.8834 | 0.7692 |
| 0.0032 | 13.0 | 169 | 0.9067 | 0.7692 |
| 0.003 | 14.0 | 182 | 0.9332 | 0.7692 |
| 0.0028 | 15.0 | 195 | 0.9511 | 0.7692 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2
- Tokenizers 0.10.3
